Dataset Information

Reversal of brain injury-induced prefrontal glutamic acid decarboxylase expression and working memory deficits by D1 receptor antagonism.

ABSTRACT: Working memory (WM), the ability to transiently hold information in mind, is essential for high-level cognitive functions that are often impaired in brain-injured patients. The cellular and molecular mechanisms contributing to WM deficits, which can manifest in the absence of overt damage, in these patients are unknown. The function of the dorsolateral prefrontal cortex in humans and monkeys, and the medial prefrontal cortex (mPFC), in rodents is critical for WM. We demonstrate that controlled cortical impact injury of rats causes a long-lasting WM impairment that is associated with increased levels of the GABA-synthesizing enzyme glutamic acid decarboxylase 67 (GAD67) in the mPFC for up to 1 month after injury. A single administration of dopamine D1 antagonists at 14 d after injury is sufficient to decrease GAD67 levels and restore WM for at least 1 week. These findings indicate that inhibition of prefrontal neuronal activity contributes to WM deficits and that strategies to reduce GAD67 expression can offer prolonged WM improvement in brain-injured patients.

SUBMITTER: Kobori N

PROVIDER: S-EPMC6673989 | biostudies-literature | 2006 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Reversal of brain injury-induced prefrontal glutamic acid decarboxylase expression and working memory deficits by D1 receptor antagonism.

Kobori Nobuhide N Dash Pramod K PK

The Journal of neuroscience : the official journal of the Society for Neuroscience 20060401 16

Working memory (WM), the ability to transiently hold information in mind, is essential for high-level cognitive functions that are often impaired in brain-injured patients. The cellular and molecular mechanisms contributing to WM deficits, which can manifest in the absence of overt damage, in these patients are unknown. The function of the dorsolateral prefrontal cortex in humans and monkeys, and the medial prefrontal cortex (mPFC), in rodents is critical for WM. We demonstrate that controlled c ...[more]

PMID: 16624944

Similar Datasets

Project description:It is well established that chronic cognitive problems after traumatic brain injury relate to diffuse axonal injury and the consequent widespread disruption of brain connectivity. However, the pattern of diffuse axonal injury varies between patients and they have a correspondingly heterogeneous profile of cognitive deficits. This heterogeneity is poorly understood, presenting a non-trivial challenge for prognostication and treatment. Prominent amongst cognitive problems are deficits in working memory and reasoning. Previous functional MRI in controls has associated these aspects of cognition with distinct, but partially overlapping, networks of brain regions. Based on this, a logical prediction is that differences in the integrity of the white matter tracts that connect these networks should predict variability in the type and severity of cognitive deficits after traumatic brain injury. We use diffusion-weighted imaging, cognitive testing and network analyses to test this prediction. We define functionally distinct subnetworks of the structural connectome by intersecting previously published functional MRI maps of the brain regions that are activated during our working memory and reasoning tasks, with a library of the white matter tracts that connect them. We examine how graph theoretic measures within these subnetworks relate to the performance of the same tasks in a cohort of 92 moderate-severe traumatic brain injury patients. Finally, we use machine learning to determine whether cognitive performance in patients can be predicted using graph theoretic measures from each subnetwork. Principal component analysis of behavioural scores confirm that reasoning and working memory form distinct components of cognitive ability, both of which are vulnerable to traumatic brain injury. Critically, impairments in these abilities after traumatic brain injury correlate in a dissociable manner with the information-processing architecture of the subnetworks that they are associated with. This dissociation is confirmed when examining degree centrality measures of the subnetworks using a canonical correlation analysis. Notably, the dissociation is prevalent across a number of node-centric measures and is asymmetrical: disruption to the working memory subnetwork relates to both working memory and reasoning performance whereas disruption to the reasoning subnetwork relates to reasoning performance selectively. Machine learning analysis further supports this finding by demonstrating that network measures predict cognitive performance in patients in the same asymmetrical manner. These results accord with hierarchical models of working memory, where reasoning is dependent on the ability to first hold task-relevant information in working memory. We propose that this finer grained information may be useful for future applications that attempt to predict long-term outcomes or develop tailored therapies.

Dataset Information

Reversal of brain injury-induced prefrontal glutamic acid decarboxylase expression and working memory deficits by D1 receptor antagonism.

Publications

Reversal of brain injury-induced prefrontal glutamic acid decarboxylase expression and working memory deficits by D1 receptor antagonism.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets